In [6]:
import cv2
import imutils
import pytesseract
from google.colab.patches import cv2_imshow
import numpy as np
image = cv2.imread('Screenshot 2024-04-17 215620.jpg')
# image = imutils.resize(image, height=500, width=500)
cv2_imshow(image)
# cv2.waitKey(0)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
cv2_imshow(gray)
# cv2.waitKey(0)
gray = cv2.GaussianBlur(gray,(5,5),0)
cv2_imshow(gray)
# cv2.waitKey(0)
# gray = cv2.bilateralFilter(gray, 101, 17, 17)
# cv2_imshow(gray)
# # cv2.waitKey(0)
edged = cv2.Canny(gray, 60, 60)
cv2_imshow(edged)
# cv2.waitKey(0)
kernel = np.ones((2, 2), np.uint8) # Create a kernel for dilation. You can adjust the size for different results.
dilated = cv2.dilate(edged, kernel, iterations=1) # Increase the number of iterations for a more pronounced effect.
cv2_imshow(dilated)
cnts, new = cv2.findContours(dilated.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
image1 = image.copy()
cv2.drawContours(image1, cnts, -1, (0, 255, 0))
cv2_imshow(image1)
# cv2.waitKey(0)
cnts = sorted(cnts, key=cv2.contourArea, reverse=True)[:30]
NumberPlateCount = None
image2 = image.copy()
cv2.drawContours(image2, cnts, -1, (0,255,0),3)
cv2_imshow(image2)
# cv2.waitKey(0)
count = 0
name = 1
for i in cnts:
perimeter = cv2.arcLength(i, True)
approx = cv2.approxPolyDP(i, 0.02*perimeter, True)
if (len(approx) == 4):
NumberPlateCount = approx
x, y, w, h = cv2.boundingRect(i)
crop_image = image[y:y+h, x:x+w]
cv2.imwrite(str(name)+ '.png', crop_image)
name += 1
break
cv2.drawContours(image, [NumberPlateCount], -1, (0,255,0),3)
cv2_imshow(image)
# cv2.waitKey(0)
# Configuration for tesseract
config = ('-l eng --oem 1 --psm 3')
# Run tesseract OCR on image
text = pytesseract.image_to_string('1.png', config=config)
# Print recognized text
print(text)
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